Modern consumer and industrial electronics, especially devices such as graphical display systems, televisions, projectors, mobile phones, portable digital assistants, navigation systems, and combination devices, are providing increasing levels of functionality to support modern life including three-dimensional display services. Research and development in the existing technologies can include many different directions.
One such direction that has received limited research and development is traffic. Little has been done to provide improved, much less enhanced, traffic information. Currently, while traffic information is available, such traffic information generally only describes the condition of a certain traffic route at the present.
Current traffic prediction systems provide an estimate of the traffic scenario along a route that is valid only at the beginning of a navigation session. This estimate may be updated as the navigation session progresses. Further these estimates are based on a limited number of data sources, like historical data, live data from users, or sensors.
Present congestion is provided primarily by traffic sensors. Future congestion is largely predicted based on present congestion, historical trends, etc. Such predictions are inherently uncertain. The effectiveness of traffic management systems would be increased by the availability of reliable predictions of the future location of commuter vehicles on the roadway.
Methodologies exist to measure or predict the traffic flow as a car moves along a particular roadway. However, such methodologies rely on long-term historical data, which is not a good predictor of future traffic flow, or are one dimensional in predicting traffic flow as a function of arrival time at a certain point. There remains a need to accurately predict road capacity at future intervals as a function of not only time, but other parameters as well.
Thus, a need still remains for an electronic system with prediction mechanism to estimate time. In view of the ever-increasing commercial competitive pressures, along with growing consumer expectations and the diminishing opportunities for meaningful product differentiation in the marketplace, it is increasingly critical that answers be found to these problems. Additionally, the need to reduce costs, improve efficiencies and performance, and meet competitive pressures adds an even greater urgency to the critical necessity for finding answers to these problems.
Solutions to these problems have been long sought but prior developments have not taught or suggested any solutions and, thus, solutions to these problems have long eluded those skilled in the art.